About this Research Topic
Environmental air, noise, and light pollution are linked to various detrimental health effects, including heart disease and premature mortality. We aim to explore the connection between environmental risk factors—such as light, noise, air pollution, and other external influences—and cardiovascular disease using animal models. While the effects of shift work and jet lag on circadian rhythms are well-studied, light pollution's impact on human biology is less understood. Technological advancements have introduced new pollution forms with harmful effects. LED light technology, for instance, makes our nights as bright as day, harming our biological health. Air and noise pollution from vehicles and other sources can disrupt circadian cycles, contributing to health problems. These environmental factors cause sleep disturbances, glucose imbalance, and high blood pressure, increasing the risk of cardiovascular issues like heart attacks, strokes, and other disorders.
Despite the significant impact of environmental risk factors on health, noise and light pollution remain poorly understood and inadequately managed. Both forms of pollution can severely affect human health by disrupting sleep and circadian rhythms, resulting in substantial social and economic consequences. By examining these relationships in animal models, scientists aim to gain insights into how similar factors may impact human cardiovascular health, potentially leading to new interventions or treatments.
The goal of this topic is to advance translational research in these critical areas, especially considering the challenges posed by climate change and an aging population that requires extended working years. This collection seeks to illuminate the often-overlooked issue of light and noise pollution, ultimately contributing to better public health strategies and improved quality of life.
This Research Topic focuses on the effects of artificial light at varying intensities during the night-day cycle, along with the physiological, genetic, and behavioral impacts of noise and air pollution. Additionally, it examines whether there are transgenerational effects in the offspring of maternal animals exposed to these environmental risks. The primary concern is how these factors influence cardiovascular health. By studying these relationships, the research aims to provide insights that could lead to better understanding and management of environmental pollution's impact on human health.
Despite the significant impact of environmental risk factors on health, noise and light pollution remain poorly understood and inadequately managed. Both forms of pollution can severely affect human health by disrupting sleep and circadian rhythms, resulting in substantial social and economic consequences. By examining these relationships in animal models, scientists aim to gain insights into how similar factors may impact human cardiovascular health, potentially leading to new interventions or treatments.
The goal of this topic is to advance translational research in these critical areas, especially considering the challenges posed by climate change and an aging population that requires extended working years. This collection seeks to illuminate the often-overlooked issue of light and noise pollution, ultimately contributing to better public health strategies and improved quality of life.
This Research Topic focuses on the effects of artificial light at varying intensities during the night-day cycle, along with the physiological, genetic, and behavioral impacts of noise and air pollution. Additionally, it examines whether there are transgenerational effects in the offspring of maternal animals exposed to these environmental risks. The primary concern is how these factors influence cardiovascular health. By studying these relationships, the research aims to provide insights that could lead to better understanding and management of environmental pollution's impact on human health.
Keywords: Animal Models, Environmental Risk Factors, Pubic Health, Cardiovascular Disease, Translational Medicine
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